First time using Scene and I was wondering if anyone had some tips on how to register a large amount of scans (200) together. I'm trying to bring together a two floor building with inside and outside with out targets. I've broken the scans into smaller clusters but seems to be chasing myself in a circle trying to bring them all together.
Thanks.
Dealing with large amount of scans
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Re: Dealing with large amount of scans
Personally, I try to break down the project into logical clusters (1st flr, 2nd flr, ext north/west, ext south/east, something like that), or if not logical then based on where I have the least overlap (splitting into two clusters based on where my overlap is weak). I register the clusters, then visually place the clusters roughly close to where they belong, and register C2C with a .5m tolerance. I find this pretty reliably allows me to place all scans, then I do a final C2C register at .1m tolerance.
Hope this helps. 200 scans is gonna take a long time, period.
Hope this helps. 200 scans is gonna take a long time, period.
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Re: Dealing with large amount of scans
200 scans is our average scan job. Break your clusters into 20-40 scans. Keep a good scan map (That helps with registration)
I am in the middle of a 3500 scan project now. Week two has finished and we have just over 2000 scans (412 GB of raw data). If anyone has tips on how to deal with a project this size that would be great.
I ran into issues with Scene on the c2c registration with a 500 scan project. "Not enough memory" My current specs are three 1-TB SSD's 64 GB physical RAM and 64 GB virtual RAM.
We plan to push the project on to NAS storage, but have not had any success with the project collaboration so for now it is still stored locally.
I am in the middle of a 3500 scan project now. Week two has finished and we have just over 2000 scans (412 GB of raw data). If anyone has tips on how to deal with a project this size that would be great.
I ran into issues with Scene on the c2c registration with a 500 scan project. "Not enough memory" My current specs are three 1-TB SSD's 64 GB physical RAM and 64 GB virtual RAM.
We plan to push the project on to NAS storage, but have not had any success with the project collaboration so for now it is still stored locally.
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Re: Dealing with large amount of scans
Hi
have a look at Scantra and the Scene plug in from Scan Taxi. This is in my opinion the fastest way and the best regarding adjustments when you are working with large amount of scans. 200 scans isn't large and should be registered in 1 to 2 days based on experience and site.
IF if need more info or like a web binare PM me.
Regards
Andrej
have a look at Scantra and the Scene plug in from Scan Taxi. This is in my opinion the fastest way and the best regarding adjustments when you are working with large amount of scans. 200 scans isn't large and should be registered in 1 to 2 days based on experience and site.
IF if need more info or like a web binare PM me.
Regards
Andrej
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Re: Dealing with large amount of scans
I never registered 3500 scans, but even 200 scan job is difficult and time consuming task for c2c registration. I usually c2c logical clusters and register those clusters using targets. Were there no spheres or paper targets used I choose overlapping scans between registered clusters and place planes, make forced correspondences in split view and register manually. It proved many times as reliable way to register large projects. If you plan right you'll get loops closed and errors distributed over the whole site in fraction of time to registering by c2c only.rsivak wrote:200 scans is our average scan job. Break your clusters into 20-40 scans. Keep a good scan map (That helps with registration)
I am in the middle of a 3500 scan project now. Week two has finished and we have just over 2000 scans (412 GB of raw data). If anyone has tips on how to deal with a project this size that would be great.
I ran into issues with Scene on the c2c registration with a 500 scan project. "Not enough memory" My current specs are three 1-TB SSD's 64 GB physical RAM and 64 GB virtual RAM.
We plan to push the project on to NAS storage, but have not had any success with the project collaboration so for now it is still stored locally.
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